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<title>LI-6800 和 LI-6400 光合数据分析指南 - 23&nbsp; 叶肉导度计算</title>
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  <ul>
<li><a href="#sec-gm-theory" id="toc-sec-gm-theory" class="nav-link active" data-scroll-target="#sec-gm-theory"><span class="header-section-number">23.1</span> 理论</a></li>
  <li><a href="#sec-constant-j" id="toc-sec-constant-j" class="nav-link" data-scroll-target="#sec-constant-j"><span class="header-section-number">23.2</span> 恒定电子流</a></li>
  <li>
<a href="#sec-variale-j" id="toc-sec-variale-j" class="nav-link" data-scroll-target="#sec-variale-j"><span class="header-section-number">23.3</span> 可变电子流</a>
  <ul class="collapse">
<li><a href="#sec-var-j-limit" id="toc-sec-var-j-limit" class="nav-link" data-scroll-target="#sec-var-j-limit"><span class="header-section-number">23.3.1</span> 可变电子流的限制因素</a></li>
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  <li><a href="#sec-intro-gm-func" id="toc-sec-intro-gm-func" class="nav-link" data-scroll-target="#sec-intro-gm-func"><span class="header-section-number">23.4</span> 函数介绍</a></li>
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<h1 class="title"><span id="sec-cal-gm" class="quarto-section-identifier"><span class="chapter-number">23</span>&nbsp; <span class="chapter-title">叶肉导度计算</span></span></h1>
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</header><p>photosynthesis` 使用了 <span class="citation" data-cites="harleyTheoreticalConsiderationsWhen1992">Harley 等 (<a href="references.html#ref-harleyTheoreticalConsiderationsWhen1992" role="doc-biblioref">1992</a>)</span> 的可变电子流的方式计算 g<sub>m</sub>，其文章中对该部分理论进行了详细介绍，在正式开始演示前，我觉得还是有必要简单复述一下其中内容，以便我们理解需要测量的参数以及这个函数的操作。</p>
<section id="sec-gm-theory" class="level2" data-number="23.1"><h2 data-number="23.1" class="anchored" data-anchor-id="sec-gm-theory">
<span class="header-section-number">23.1</span> 理论</h2>
<p>从大气中 CO<sub>2</sub> 扩散到叶绿体中分压的下降与每个步骤的导度成反比：</p>
<p><span id="eq-diffuse"><span class="math display">
A=(C_a - C_i) \cdot g_s/P = (C_i - C_c) \cdot g_m/P
\tag{23.1}</span></span></p>
<p>这里 P 指的是大气压。这个关于气体扩散的定理自然是后面计算所需的基石。之所以使用分压，是因为气体扩散经过叶肉细胞时，叶肉细胞内是液相空间，而根据 Henry’s law:</p>
<p><span id="eq-henry-law"><span class="math display">
P \propto C (or) P = k_H \cdot C
\tag{23.2}</span></span></p>
<p>也就是描述气体溶于水的量，与其分压成正比。</p>
<p>而对于 FvCB 模型，我们一般都认为 RuBP 的羧化受到下面三个因子的限制：</p>
<ol type="1">
<li>Rubisco 的活性，</li>
<li>RuBP 的再生（或者称为为 J 限制），</li>
<li>磷酸丙糖代谢为淀粉或蔗糖时正磷酸盐的释放</li>
</ol>
<p>当 Rubisco 限制阶段，光合作用的描述是：</p>
<p><span id="eq-rubisco-limit"><span class="math display">
A = \frac{V_{cmax} \cdot C_c}{C_c + K_c \cdot (1+O/K_O)} \cdot \bigg(1-\frac{\Gamma^*}{C_c} \bigg) - R_d
\tag{23.3}</span></span></p>
<p>根据 Henry’s law 替换 C<sub>c</sub>：</p>
<p><span id="eq-cc-henry"><span class="math display">
A = \frac{V_{cmax} \cdot (C_i - A/g_m)}{C_c + K_c \cdot (1+O/K_O)} \cdot \bigg(1-\frac{\Gamma^*}{C_i - A/g_m)} \bigg) - R_d
\tag{23.4}</span></span></p>
<p>当处于 RuBP 限制阶段时：</p>
<p><span id="eq-rubp-limit"><span class="math display">
A = J \cdot \frac{(C_i - A/g_m) - \Gamma^*}{4 \cdot ((C_i - A/g_m) +2\Gamma^*)} - R_d
\tag{23.5}</span></span></p>
<p>而电子传递速率可以通过辐射的光量子密度来计算：</p>
<p><span id="eq-cal-j"><span class="math display">
J = \frac{0.24 \quad PPFD}{(1+0.24^2 \cdot PPFD^2 / J_{max})^{0.5}}
\tag{23.6}</span></span></p>
<p>而 RuBP 限制阶段的公式也可以用写为电子传递速率的形式：</p>
<p><span id="eq-rubp-j"><span class="math display">
J = (A+R_d) \cdot\frac{4 \cdot ((C_i - A/g_m) + 2 \Gamma^*)}{(C_i - A/g_m)-\Gamma^*}
\tag{23.7}</span></span></p>
<p>观察上面的公式我们可以看到，这个公式的适用性很广。而计算叶肉导度的方法，不管是可变电子流还是恒定电子流，都与其密切相关。</p>
</section><section id="sec-constant-j" class="level2" data-number="23.2"><h2 data-number="23.2" class="anchored" data-anchor-id="sec-constant-j">
<span class="header-section-number">23.2</span> 恒定电子流</h2>
<p>恒定电子流的假设是 J 不随 CO<sub>2</sub> 的分压而改变。因而，需要一个荧光二氧化碳响应曲线来确定 J 不随 CO<sub>2</sub> 而变化的范围。一个共识是认为当 PPFD 和其他淬灭参数不变时， J 是恒定的，如果光强小于饱和的 PPFD，很容易得到更广范围的 CO<sub>2</sub> 分压下 J 是否恒定。该方法尽管存在限制，但是他的优势是可以基于多个气体交换的测量进行计算，从而降低单个测量的误差。</p>
</section><section id="sec-variale-j" class="level2" data-number="23.3"><h2 data-number="23.3" class="anchored" data-anchor-id="sec-variale-j">
<span class="header-section-number">23.3</span> 可变电子流</h2>
<p>对于可变电子流，只是认为 J 是变化的，但是 J 可以通过叶绿素荧光测量直接获得。</p>
<p><span id="eq-var-j"><span class="math display">
g_m = \frac{A}{C_i - \frac{\Gamma^*[J+ 8 \cdot(A+ R_d)]}{J - 4 \cdot (A + R_d)}}
\tag{23.8}</span></span></p>
<p>该方法测量相比来说比较简单。</p>
<section id="sec-var-j-limit" class="level3" data-number="23.3.1"><h3 data-number="23.3.1" class="anchored" data-anchor-id="sec-var-j-limit">
<span class="header-section-number">23.3.1</span> 可变电子流的限制因素</h3>
<p>恒定电子流可以在一系列大的 CO<sub>2</sub> 跨度下使用，但是要解决 CO<sub>2</sub> 对 g<sub>m</sub> 影响的问题，则需要可变电子流的方式。但是可变电子流中参数 R<sub>d</sub>，<span class="math inline">\Gamma^*</span> 存在不确定性，而对 J 的计算错误则导致整个计算错误。因而作者确定了一个通过 C<sub>c</sub> 对 (A+R<sub>d</sub>) 斜率的阈值进行判定的计算叶肉导度是否合理的方法。因为：</p>
<p><span id="eq-cc-j-judge"><span class="math display">
C_c = \Gamma^*[J+8\cdot(A+R_d)]/[J-4 \cdot(A+R_d)]
\tag{23.9}</span></span></p>
<p>那么：</p>
<p><span id="eq-j-finall"><span class="math display">
dC_c/dA = 12 \cdot \Gamma^* \cdot J/[J - 4 \cdot(A+R_d)]^2
\tag{23.10}</span></span></p>
<p>最终确认的有限的计算数据必须满足 <span class="math inline">10 &lt; dC_c/dA &lt; 50</span>。这是 <code>fit_g_mc_variable</code> 所采用的合理的叶肉导度相关列所必须满足的条件。</p>
</section></section><section id="sec-intro-gm-func" class="level2" data-number="23.4"><h2 data-number="23.4" class="anchored" data-anchor-id="sec-intro-gm-func">
<span class="header-section-number">23.4</span> 函数介绍</h2>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb1"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="fu">fit_g_mc_variableJ</span><span class="op">(</span></span>
<span>  <span class="va">data</span>,</span>
<span>  varnames <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>A_net <span class="op">=</span> <span class="st">"A_net"</span>, J_etr <span class="op">=</span> <span class="st">"J_etr"</span>, C_i <span class="op">=</span> <span class="st">"C_i"</span>, PPFD <span class="op">=</span> <span class="st">"PPFD"</span>,</span>
<span>    phi_PSII <span class="op">=</span> <span class="st">"phi_PSII"</span><span class="op">)</span>,</span>
<span>  usealpha_Q <span class="op">=</span> <span class="cn">FALSE</span>,</span>
<span>  alpha_Q <span class="op">=</span> <span class="fl">0.84</span>,</span>
<span>  beta_Q <span class="op">=</span> <span class="fl">0.5</span>,</span>
<span>  <span class="va">gamma_star</span>,</span>
<span>  <span class="va">R_d</span>,</span>
<span>  P <span class="op">=</span> <span class="fl">100</span></span>
<span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
<p>函数本身参数都比较简单。函数有一个计算数据可靠性的检测，并只使用它检测有效的数据进行拟合进行取平均值，而且他计算的单位是按分压计算的：<span class="math inline">m^{-2} \cdot s^{-1} \cdot Pa^{-1}</span>。</p>
<p>我使用软件包自带的数据进行演示，当然了 LI-6400 也是可以的，但请参考开始的连接中的文章，来进行相应处理，首先是加载软件包，我们顺便看一下数据：</p>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb2"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/cdmuir/photosynthesis">photosynthesis</a></span><span class="op">)</span></span>
<span><span class="va">gm_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/utils/read.table.html">read.csv</a></span><span class="op">(</span><span class="st">"data/A_Ci_Q_data_1.csv"</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
<p>然后进行拟合就可以了：</p>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb3"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/photosynthesis/man/fit_g_mc_variableJ.html">fit_g_mc_variableJ</a></span><span class="op">(</span></span>
<span>  <span class="va">gm_data</span>,</span>
<span>  varnames <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span></span>
<span>    A_net <span class="op">=</span> <span class="st">"A"</span>,</span>
<span>    J_etr <span class="op">=</span> <span class="st">"ETR"</span>,</span>
<span>    C_i <span class="op">=</span> <span class="st">"Ci"</span>,</span>
<span>    PPFD <span class="op">=</span> <span class="st">"Qin"</span>,</span>
<span>    phi_PSII <span class="op">=</span> <span class="st">"PhiPS2"</span></span>
<span>  <span class="op">)</span>,</span>
<span>  gamma_star <span class="op">=</span> <span class="fl">46</span>,</span>
<span>  R_d <span class="op">=</span> <span class="fl">0.153</span>,</span>
<span>  usealpha_Q <span class="op">=</span> <span class="cn">TRUE</span>,</span>
<span>  alpha_Q <span class="op">=</span> <span class="fl">0.84</span>,</span>
<span>  beta_Q <span class="op">=</span> <span class="fl">0.5</span>,</span>
<span>  P <span class="op">=</span> <span class="fl">84</span></span>
<span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
<p>我们可以看一下 <code>data</code> 前的数据，仅显示 gsw 和 g_mc(计算的叶肉导度)：</p>
<div class="cell">
<div class="cell-output-display">
<table class="table table-sm table-striped small">
<thead><tr class="header">
<th style="text-align: right;">gsw</th>
<th style="text-align: right;">g_mc</th>
</tr></thead>
<tbody>
<tr class="odd">
<td style="text-align: right;">0.3458193</td>
<td style="text-align: right;">1.1366292</td>
</tr>
<tr class="even">
<td style="text-align: right;">0.3409737</td>
<td style="text-align: right;">1.0829398</td>
</tr>
<tr class="odd">
<td style="text-align: right;">0.3460976</td>
<td style="text-align: right;">1.1646861</td>
</tr>
<tr class="even">
<td style="text-align: right;">0.3666962</td>
<td style="text-align: right;">1.0234578</td>
</tr>
<tr class="odd">
<td style="text-align: right;">0.3977929</td>
<td style="text-align: right;">-0.5338358</td>
</tr>
<tr class="even">
<td style="text-align: right;">0.4284309</td>
<td style="text-align: right;">0.8689417</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>可以看到，是有很多不合理值的，我们可以作图看一下合理的值：</p>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb4"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span><span class="op">(</span><span class="va">data</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">CO2_s</span>, y <span class="op">=</span> <span class="va">g_mc</span>, colour <span class="op">=</span> <span class="va">reliable</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">CO</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span><span class="op">~</span><span class="st">"("</span><span class="op">*</span><span class="va">mu</span><span class="op">*</span><span class="va">mol</span><span class="op">~</span><span class="va">mol</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">")"</span><span class="op">)</span>,</span>
<span>       y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">g</span><span class="op">[</span><span class="va">m</span><span class="op">]</span><span class="op">~</span><span class="st">"(mol"</span><span class="op">~</span><span class="va">m</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">2</span><span class="op">}</span><span class="op">~</span><span class="va">s</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">~</span><span class="va">Pa</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">")"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html">geom_point</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">'bottom'</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details><div class="cell-output-display">
<div id="fig-gmc-plot-reasonable" class="quarto-figure quarto-figure-center quarto-float anchored">
<figure class="quarto-float quarto-float-fig figure"><div aria-describedby="fig-gmc-plot-reasonable-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="gm_files/figure-html/fig-gmc-plot-reasonable-1.png" class="img-fluid figure-img" width="672">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-gmc-plot-reasonable-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
Figure&nbsp;23.1: 使用默认作图查看合理值
</figcaption></figure>
</div>
</div>
</div>
<p>当然上面的作图来自于 <code>vignette</code>，如果与我一样还没赶上潮流，可以使用 <code>base plot</code>：</p>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb5"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="va">col_sep</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html">ifelse</a></span><span class="op">(</span><span class="va">data</span><span class="op">$</span><span class="va">reliable</span> <span class="op">==</span> <span class="cn">TRUE</span>, <span class="st">"#56B4E9"</span>, <span class="st">"#CC79A7"</span><span class="op">)</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span><span class="op">(</span><span class="va">data</span>, <span class="op">{</span></span>
<span>  <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="va">CO2_s</span>, <span class="va">g_mc</span>, col <span class="op">=</span> <span class="va">col_sep</span>, </span>
<span>       xlab <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">CO</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span><span class="op">~</span><span class="st">"("</span><span class="op">*</span><span class="va">mu</span><span class="op">*</span><span class="va">mol</span><span class="op">~</span><span class="va">mol</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">")"</span><span class="op">)</span>,</span>
<span>       ylab <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">g</span><span class="op">[</span><span class="va">m</span><span class="op">]</span><span class="op">~</span><span class="st">"(mol"</span><span class="op">~</span><span class="va">m</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">2</span><span class="op">}</span><span class="op">~</span><span class="va">s</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">~</span><span class="va">Pa</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">")"</span><span class="op">)</span>,</span>
<span>       pch <span class="op">=</span><span class="fl">19</span>, cex <span class="op">=</span> <span class="fl">0.8</span><span class="op">)</span></span>
<span>  <span class="fu"><a href="https://rdrr.io/r/graphics/legend.html">legend</a></span><span class="op">(</span><span class="st">'bottomright'</span>, legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">'TRUE'</span>,<span class="st">'FALSE'</span><span class="op">)</span>, pch <span class="op">=</span> <span class="fl">19</span>, col <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"#56B4E9"</span>, <span class="st">"#CC79A7"</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="op">}</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details><div class="cell-output-display">
<div id="fig-gmc-base-reasonable" class="quarto-figure quarto-figure-center quarto-float anchored">
<figure class="quarto-float quarto-float-fig figure"><div aria-describedby="fig-gmc-base-reasonable-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="gm_files/figure-html/fig-gmc-base-reasonable-1.png" class="img-fluid figure-img" width="672">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-gmc-base-reasonable-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
Figure&nbsp;23.2: 使用基础作图查看合理值
</figcaption></figure>
</div>
</div>
</div>
<p>查看前文所讲的斜率判定相关数据：</p>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb6"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="co">#Plot QAQC graph according to Harley et al. 1992</span></span>
<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span><span class="op">(</span><span class="va">data</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">CO2_s</span>, y <span class="op">=</span> <span class="va">dCcdA</span>, colour <span class="op">=</span> <span class="va">reliable</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">CO</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span><span class="op">~</span><span class="st">"("</span><span class="op">*</span><span class="va">mu</span><span class="op">*</span><span class="va">mol</span><span class="op">~</span><span class="va">mol</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">")"</span><span class="op">)</span>,</span>
<span>       y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">delta</span><span class="op">*</span><span class="va">C</span><span class="op">[</span><span class="va">c</span><span class="op">]</span><span class="op">*</span><span class="st">"/"</span><span class="op">*</span><span class="va">delta</span><span class="op">*</span><span class="va">A</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html">geom_hline</a></span><span class="op">(</span>yintercept <span class="op">=</span> <span class="fl">10</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html">geom_point</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">'bottom'</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details><div class="cell-output-display">
<div id="fig-dccda-quality" class="quarto-figure quarto-figure-center quarto-float anchored">
<figure class="quarto-float quarto-float-fig figure"><div aria-describedby="fig-dccda-quality-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="gm_files/figure-html/fig-dccda-quality-1.png" class="img-fluid figure-img" width="672">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-dccda-quality-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
Figure&nbsp;23.3: 外界二氧化碳浓度与判定用斜率作图
</figcaption></figure>
</div>
</div>
</div>
<div class="cell">
<details open="" class="code-fold"><summary>Code</summary><div class="sourceCode" id="cb7"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span><span class="op">(</span><span class="va">data</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">dCcdA</span>, y <span class="op">=</span> <span class="va">g_mc</span>, colour <span class="op">=</span> <span class="va">reliable</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">delta</span><span class="op">*</span><span class="va">C</span><span class="op">[</span><span class="va">c</span><span class="op">]</span><span class="op">*</span><span class="st">'/'</span><span class="op">*</span><span class="va">delta</span><span class="op">*</span><span class="va">A</span><span class="op">)</span>,</span>
<span>       y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html">expression</a></span><span class="op">(</span><span class="va">g</span><span class="op">[</span><span class="va">m</span><span class="op">]</span><span class="op">~</span><span class="st">'(mol'</span><span class="op">~</span><span class="va">m</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">2</span><span class="op">}</span><span class="op">~</span><span class="va">s</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">~</span><span class="va">Pa</span><span class="op">^</span><span class="op">{</span><span class="op">-</span><span class="fl">1</span><span class="op">}</span><span class="op">*</span><span class="st">')'</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html">geom_point</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">'bottom'</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details><div class="cell-output-display">
<div id="fig-gmc-quality-" class="quarto-figure quarto-figure-center quarto-float anchored">
<figure class="quarto-float quarto-float-fig figure"><div aria-describedby="fig-gmc-quality--caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="gm_files/figure-html/fig-gmc-quality--1.png" class="img-fluid figure-img" width="672">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-gmc-quality--caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
Figure&nbsp;23.4: 判定用斜率与叶肉导度作图
</figcaption></figure>
</div>
</div>
</div>
<p>这里数据都已经包含在拟合数据里，想怎么作图可以随意定制。</p>


<div id="refs" class="references csl-bib-body hanging-indent" data-entry-spacing="0" role="list" style="display: none">
<div id="ref-harleyTheoreticalConsiderationsWhen1992" class="csl-entry" role="listitem">
Harley, Peter C., Francesco Loreto, Giorgio Di Marco, 和 Thomas D. Sharkey. 1992. <span>《Theoretical <span>Considerations</span> when <span>Estimating</span> the <span>Mesophyll</span> <span>Conductance</span> to <span>CO2</span> <span>Flux</span> by <span>Analysis</span> of the <span>Response</span> of <span>Photosynthesis</span> to <span>CO2</span>》</span>. <em>Plant Physiology</em> 98: 1429–36.
</div>
</div>
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